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Predicting productivity of Acacia hybrid plantations for a range of climates and soils in Vietnam

journal contribution
posted on 2023-05-18, 17:32 authored by Thai Hung, T, Almeida, AC, Alieta EylesAlieta Eyles, Caroline MohammedCaroline Mohammed
Acacia hybrid (A. auriculiformis × A. mangium) has rapidly become the most widely planted species in Vietnam for the production of pulpwood and sawlogs. As it is adapted to the very wide range of site and soil conditions that prevail throughout the country, providing an ability to predict accurately its productivity is an essential part of optimising product value and income to growers. In this study, we calibrated the 3-PG growth model using ten permanent sample plots located in stands aged 1, 3 and 6 yr. The model was then validated using 55 additional permanent plots from 12 plantations growing in four regions that support plantation forestry. The model performed well for most of the validation sites; model efficiencies (EF) were ⩾0.76. The model was more accurate in predicting the productivity of plantations in the North and North Central Coast than in the South and South Central Coast regions. Growth was most affected by soil water deficit in this wet/dry tropical environment, than by temperature, particularly in the North. Soil fertility was best predicted by a relationship with soil organic carbon and the base cations Ca++ and K+. Across regions, the mean current monthly increment of stand volume for a 15-yr rotation was 3.21 and 1.97 m3 ha−1 month−1 for the wet and dry seasons, respectively. Sensitivity analysis indicated how much the model parameters affect the main outputs and how this changes with stand age. Overall, the model provided an accurate description of the potential productivity of Acacia hybrid plantations across a wide range of climates and soils in Vietnam.


Publication title

Forest Ecology and Management








Tasmanian Institute of Agriculture (TIA)


Elsevier BV

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Copyright 2016 Elsevier B.V.

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Socio-economic Objectives

Hardwood plantations

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